Modern data warehouse

Modern data warehouse solutions from Microsoft help you find new insights from Big Data by seamlessly combining traditional high volume relational stores with new data stores for unstructured data like Hadoop.

Handle data of all volumes with a modern data warehouse

With traditional data warehouse technologies, your scale is capped and you’ll need to buy new hardware as more capacity is required. The Microsoft modern data warehouse scales to the most demanding enterprise requirements. As data requirements grow, you can scale from tens of terabytes up to the multi-petabytes by incrementally adding nodes to your existing infrastructure.

To boost its competitiveness, the company sought to increase its data warehouse performance, so it could deliver store-level purchasing data more quickly to its business analysts and managers.

Virginia Tech transforms life sciences research with big data solution in the cloud

A team of computer scientists at Virginia Tech developed an on-demand, cloud-computing model using the Microsoft Azure HDInsight Service. By moving to an on-demand cloud computing model, they will now have easier, more cost-effective access to DNA sequencing tools and resources.

Capabilities

Shared nothing architecture

Massive parallel processing in Parallel Data Warehouse leverages a ‘shared nothing’ architecture where there are multiple physical nodes; each running its own instance of SQL Server with dedicated CPU, memory, and storage. This results in performance many times faster than traditional architectures.

Microsoft Azure storage blobs

Microsoft Azure HDInsight leverages an elastic cloud infrastructure that stores data in Azure storage blobs. This gives users the ability to store any amount of data within Azure.

Scale Hadoop clusters independent of storage

Microsoft Azure HDInsight has an architecture that separates the Hadoop cluster from the data storage. This allows users to scale the Hadoop cluster up or down on the fly or have multiple Hadoop clusters processing the same data.